The utility of LENA as an indicator of developmental outcomes for young children with autism

There is growing understanding of the potential benefits of a multi-method approach to accurately capture language skills of children on the autism spectrum. Tools such as Language ENvironment Analysis (LENA) provide an efficient means of capturing and analysing early child vocalizations (CVs) and the language learning environment. While developed to capture whole-day recordings of child language in naturalistic settings, there is potential utility in capturing, but little knowledge about, primary LENA metrics-including CVs and conversational turns (CTs)-and novel metrics, such as vocalization ratios (VRs), sampled in clinical practice settings where children are often seen. Moreover, recent research indicates that the novel VR may offer a broad indicator of children's developmental level, beyond just their language abilities, a hypothesis yet to be investigated in a large sample of children for whom the LENA was designed (i.e., pre-schoolers).

To explore the extent to which primary and novel LENA metrics collected during brief one-to-one clinical interaction was a useful indicator of developmental outcomes for children on the autism spectrum.

Participants were recruited as part of an on-going research programme evaluating early intervention outcomes (n = 99; age 14-47 months). Language samples were collected at intake (T1) using the wearable LENA Digital Language Processors during a one-to-one, play-based assessment with a clinician. Direct (Mullen Scales of Early Learning-MSEL) and parent-report (Vineland Adaptive Behavior Scales-VABS) measures of verbal and non-verbal skills were also collected at intake (T1) and again at exit (T2), approximately 12 months later.

Few correlations were observed between child measures and CVs, a primary LENA metric. The novel VR metric was associated with concurrent direct assessment (MSEL) (and to a lesser extent parent report; VABS) measures of verbal and non-verbal skills, with moderate positive correlations found between VRs and all directly assessed subscale scores. However, VRs did not uniquely contribute to the prediction of child outcomes when baseline skills were also considered.

The novel VR may provide an insight into autistic children's overall development in addition to their language ability, suggesting that even when collected in a short recording format, LENA might be a useful component of a multi-method assessment approach.

What is already known on the subject To accurately capture language skills of children on the autism spectrum, multi-method approaches, including natural language sampling, are recommended. Tools such as LENA provide an efficient means of capturing and analysing naturalistic child language and the language learning environment. What this paper adds to existing knowledge This study demonstrates the potential benefits, and limitations, of using LENA to augment assessment of young children on the autism spectrum. Specifically, LENA provides a complementary, and low burden, method for capturing child language samples. What are the potential or actual clinical implications of this work? Novel metrics, such as the VR, collected during brief clinical interactions might be a useful component of a multi-method assessment approach for children on the autism spectrum.